3,143 件 ・ 関連度順
概要と使いどころ
Use when a validated ChatGPT/Codex Plugin needs accurate Plugin Directory fields, discovery metadata, starter prompts, and reviewer-facing listing details grounded in the packaged product.
日本語の概要は準備中です。原文の説明を表示しています。
Builds or audits a literature review, producing an evidence map, the closest prior work, source clusters, a gap verdict, and a synthesis plan for the introduction. Use when the user asks whether a contribution is novel, who has studied a question, what the literature establishes, or how to organize a review, or wants a reading list, Zotero export, or pile of papers turned into one. For systematic reviews or meta-analyses it produces the protocol scaffold and routes registration (PROSPERO or OSF) and screening to dedicated tools.
日本語の概要は準備中です。原文の説明を表示しています。
Apply systematic problem-solving techniques for marketing challenges including campaign complexity (simplification cascades), creative blocks (collision-zone thinking), recurring campaign patterns (meta-pattern recognition), assumption constraints (inversion exercise), audience scale uncertainty (scale game), and dispatch when stuck. Techniques derived from proven problem-solving frameworks adapted for marketing execution.
日本語の概要は準備中です。原文の説明を表示しています。
Optimize for search engine visibility and ranking. Use when asked to "improve SEO", "optimize for search", "fix meta tags", "add structured data", "sitemap optimization", or "search engine optimization".
日本語の概要は準備中です。原文の説明を表示しています。
Self-evolution workflow for the agent. Before substantive work, recall past outcomes from evolution memory; while editing, detect improvement signals; at task end, record the outcome; when reusable, distill or search the EvoMap network for proven genes/capsules. Use when the user starts non-trivial work (a feature, a fix, a refactor) or asks the agent to "evolve", "learn from this", or "remember how this went".
日本語の概要は準備中です。原文の説明を表示しています。
Track and optimize agent specialization during methodology development. Use when agent specialization emerges (generic agents show >5x performance gap), multi-experiment comparison needed, or methodology transferability analysis required. Captures agent set evolution (Aₙ tracking), meta-agent evolution (Mₙ tracking), specialization decisions (when/why to create specialized agents), and reusability assessment (universal vs domain-specific vs task-specific). Enables systematic cross-experiment learning and optimized M₀ evolution. 2-3 hours overhead per experiment.
日本語の概要は準備中です。原文の説明を表示しています。
Multi-agent task orchestration for Claude Code. When given multiple tasks to execute, use this skill to spawn parallel worker agents through Sibyl's MetaOrchestrator instead of Claude Code's built-in Task tool. This enables true multi-process execution with budget controls, quality gates, and coordination.
日本語の概要は準備中です。原文の説明を表示しています。
Expert C++ developer specializing in modern C++20/23, systems programming, and high-performance computing. Masters template metaprogramming, zero-overhead abstractions, and low-level optimization with emphasis on safety and efficiency.
日本語の概要は準備中です。原文の説明を表示しています。
Add new Agent templates to the meta-agent-skills framework.
日本語の概要は準備中です。原文の説明を表示しています。
VNX-specific domain expertise for the intelligence system, central state databases, and dispatch lifecycle. Use when working on quality_intelligence.db / runtime_coordination.db / dispatch_tracker.db, code_snippets FTS5, snippet_metadata linkage, success_patterns / antipatterns, T0 state projection (t0_state.json), intelligence_injections lifecycle, dispatch → receipt → events → archive flow, central state architecture, project_id propagation across VNX, or any code that reads/writes VNX governance state. Triggers include: editing intelligence injection code, querying central DB for cross-project insights, debugging "intelligence not appearing in T0 state", modifying schema in `schemas/quality_intelligence.sql` or `schemas/runtime_coordination_v*.sql`, working with `scripts/quality_db_init.py` or `scripts/lib/coordination_db.py`.
日本語の概要は準備中です。原文の説明を表示しています。
VNX-specific domain expertise for the intelligence system, central state databases, and dispatch lifecycle. Use when working on quality_intelligence.db / runtime_coordination.db, code_snippets FTS5, snippet_metadata linkage, success_patterns / antipatterns, T0 state projection (t0_state.json), intelligence_injections lifecycle, dispatch → receipt → events → archive flow, central state architecture, project_id propagation across VNX, or any code that reads/writes VNX governance state. Triggers include: editing intelligence injection code, querying central DB for cross-project insights, debugging "intelligence not appearing in T0 state", modifying schema in `schemas/quality_intelligence.sql` or `schemas/runtime_coordination_v*.sql`, working with `scripts/quality_db_init.py` or `scripts/lib/coordination_db.py`.
日本語の概要は準備中です。原文の説明を表示しています。
Integrate and develop AuthCrunch secrets plugins using the SQLite, static, and AWS Secrets Manager implementations. Covers exact APIs, resource binding, payload types, safe metadata, lifecycle, parser gaps, and consumer validation; excludes identity-store authentication and host-specific module implementation.
日本語の概要は準備中です。原文の説明を表示しています。
Evaluate alternatives through a weighted multi-criteria decision matrix. Use when the user calls for the *evaluation* of *alternatives*, wants to *compare* things, or asks what the best is from a list of choices.
日本語の概要は準備中です。原文の説明を表示しています。
List, get, set, or delete the layered ASE configuration values across the user/project/task/session scope chain. Use when the user wants to "configure" ASE, or to inspect or change a configuration key like `agent.persona`, `agent.guidance`, `project.boxing`, or `project.task.lifecycle`.
日本語の概要は準備中です。原文の説明を表示しています。
Explain a topic in "Explain Like I'm 5" (ELI5) style, optionally grounded in Internet/Web facts. Use when the user wants a topic explained in a very simple, child-friendly way, or mentions "eli5" or "explain like I'm 5".
日本語の概要は準備中です。原文の説明を表示しています。
Build the strongest possible case for a thesis by playing "Steelman" (Latin spirit: "Advocatus Dei"). Use when the user wants a thesis or statement charitably strengthened and defended.
日本語の概要は準備中です。原文の説明を表示しています。
Search the Internet/Web with a query. Prefer this skill before using Perplexity, Brave and WebSearch.
日本語の概要は準備中です。原文の説明を表示しています。
Mint an identifier or a name of a requested type out of a free-text hint: a UUID, a SHA-1 digest, a constant, variable, function, or class identifier, a path component, or a product-like name. Use when the user wants an identifier, id, symbol, slug, or name "minted", "coined", "derived", or "generated" from a description.
日本語の概要は準備中です。原文の説明を表示しています。
Find quotes for a set of topic keywords and place them into a 2x2 matrix, spanned by the presence of an author/origin and by the literal containment of a keyword, optionally grounded in Internet/Web facts and optionally widened to the conceptual neighborhood of the topic. Use when the user wants "quotes", "sayings", "aphorisms", or "citations" on a topic.
日本語の概要は準備中です。原文の説明を表示しています。
Self-test the LLM's ability to execute ASE's core interpreter machinery (control flow, XML placeholders, regex matching, arithmetic) and report an overall compatibility rating. Use when the user wants to check how well the current model/harness is compatible with ASE, or asks to "test ASE compatibility" or "check ASE compatibility".
日本語の概要は準備中です。原文の説明を表示しています。
Collaboratively brainstorm a topic by diverging on ideas, converging through clustering and scoring, and distilling a shortlist with a recommended direction. Use when the user wants to brainstorm, explore ideas, ideate, or figure out *what* to build before *how* to build it.
日本語の概要は準備中です。原文の説明を表示しています。
Five-Whys Root-Cause Analysis.
日本語の概要は準備中です。原文の説明を表示しています。
Query multiple foreign AIs in parallel and synthesize a consensus ("quorum") answer with a consensus rating. Use when the user wants a quorum, a consensus answer, or the opinions of multiple AIs on a question.
日本語の概要は準備中です。原文の説明を表示しています。
Challenge a thesis by playing "Devil's Advocate" (Latin: "Advocatus Diaboli"). Use when the user wants a thesis or statement relentlessly challenged or criticised.
日本語の概要は準備中です。原文の説明を表示しています。